Deep Learning for Market by Order Data
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DOI: 10.1080/1350486X.2021.1967767
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Cited by:
- Ilia Zaznov & Julian Kunkel & Alfonso Dufour & Atta Badii, 2022. "Predicting Stock Price Changes Based on the Limit Order Book: A Survey," Mathematics, MDPI, vol. 10(8), pages 1-33, April.
- Antonio Briola & Silvia Bartolucci & Tomaso Aste, 2024. "HLOB -- Information Persistence and Structure in Limit Order Books," Papers 2405.18938, arXiv.org, revised Jun 2024.
- Briola, Antonio & Bartolucci, Silvia & Aste, Tomaso, 2025. "HLOB–Information persistence and structure in limit order books," LSE Research Online Documents on Economics 126623, London School of Economics and Political Science, LSE Library.
- Peer Nagy & Jan-Peter Calliess & Stefan Zohren, 2023. "Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets," Papers 2301.08688, arXiv.org, revised Sep 2023.
- Jian Guo & Heung-Yeung Shum, 2024. "Large Investment Model," Papers 2408.10255, arXiv.org, revised Aug 2024.
- Mahmut Bağcı & Pınar Kaya Soylu & Selçuk Kıran, 2024. "The Symmetric and Asymmetric Algorithmic Trading Strategies for the Stablecoins," Computational Economics, Springer;Society for Computational Economics, vol. 64(5), pages 2663-2684, November.
- Konark Jain & Nick Firoozye & Jonathan Kochems & Philip Treleaven, 2024. "Limit Order Book Simulations: A Review," Papers 2402.17359, arXiv.org, revised Mar 2024.
- Petter N. Kolm & Jeremy Turiel & Nicholas Westray, 2023. "Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book," Mathematical Finance, Wiley Blackwell, vol. 33(4), pages 1044-1081, October.
- Zihao Zhang & Stefan Zohren, 2021. "Multi-Horizon Forecasting for Limit Order Books: Novel Deep Learning Approaches and Hardware Acceleration using Intelligent Processing Units," Papers 2105.10430, arXiv.org, revised Aug 2021.
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